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I've always been fascinated by technology. I never became a programmer or developer. Built a few websites in my time, but that wasn't where my talents were hiding. Instead, I would say I've always been an impressed observer. Impressed not only by the bells and whistles and shiny objects technology offered, but by the results it achieved for people and companies.

When we all first started talking about artificial intelligence (AI), it was in end-of-the-world scenarios and science fiction. There was H.A.L. from "2001: A Space Odyssey" and SkyNet from "Terminator" fame. Slowly, over the course of decades, in fact, both presentation and perception evolved. And suddenly, there were friendly, useful examples, like the chatbot that answered your questions on your bank's website or Pixar's "Wall-e."

My, how times have changed.

These days, AI isn't just about embedding a fancy conversational chatbot in your website. It's a tempo reset. Amazon has used it to personalize every interaction (no matter how minor), and Apple's iPhones are now routinely summarizing 45 group text messages for me into one simple sentence. Insurers are using it too, but so far in a much more pedestrian manner.

Going forward, insurers need to move from using AI to identify trends and automate processes to using it for lifelike reactions to modern life. Part of the challenge here will be for insurers to recognize that it's not enough to simply keep pace with policyholders today. The insurers able to use AI to outpace policyholders, to provide convenient solutions to everyday problems, those are the companies who will win business in 2026, 2027, and beyond.

Here are three ways insurers can use AI to edge into a competitive position.

  1. Detect lifestyle shifts proactively. When claims start to roll in, it's too late to detect a trend. On the front end, generative and predictive AI can analyze behavioral data from gig-platforms, housing migration trends, telematics products, and purchase signals to spot emerging lifestyle shifts before loss ratios are affected. Insurers using AI-based "trend detection" have already improved product speed-to-market by as much as 35 percent, according to McKinsey's 2025 State of AI in Insurance report.
  2. Personalize products at the speed of behavior. AI-driven personalization solutions can dynamically match product definition to real-time customer context. In fact, insurers using machine learning (ML) to personalize coverage achieved 20% to 25% higher retention and 15 percent lower acquisition costs as reported in a 2024 Accenture report.This is especially significant since the acquisition of net new customers, or customer acquisition cost (CAC), is so high in a complex sale situation, like insurance.
  3. Streamline complexity so humans can reimagine protection. Much like my example of how my iPhone summarizes group texts and presents the most cogent points, retrieval-augmented generation (RAG) models can synthesize underwriting guidelines and claim notes into actionable insights, freeing staff to focus on innovation. Deloitte's 2025 Insurance Outlook predicts that insurers using AI for knowledge retrieval will reduce time-to-quote and time-to-launch by up to 40%.

These challenges and opportunities exist because insurance has never been a "set it and forget it" product. It's a living promise that's supposed to keep up (and empower) modern lifestyles — and right now, modern life is changing faster than most insurers can comprehend (let alone re-rate a book of business).

AI is the first tool we've had that can compress that lag time. Not by making insurers feel innovative, but by making them behave like the rest of the world (looking at you, Amazon) already does. When insurers start sensing change early, responding in real time, and removing friction without asking customers to become insurance experts, that's the tipping point for AI in this industry.

Insurers must move from pedestrian dashboard creation and chatbot integration immediately. With AI, trend detection can help insurers see around blind corners. Personalization can turn textbook coverages into something that feels both bespoke and comfortable instead of an impersonal transaction. And knowledge retrieval can clear operational clutter so full-time employees (FTEs) can stop babysitting processes and start designing better protection products.

This isn't a future-state vision. It's a 2026 survival strategy. The insurers treating AI as a true operating model will earn customer trust, loyalty, and referrals. The rest will keep optimizing yesterday, right up until tomorrow cancels them.

Jennifer Overhulse is the owner of St. Nick Media Services. She can be reached for further information or comment via email at jen@stnickmedia.com.

Opinions expressed here are the author's own.

(Image credit: Adobe Stock)

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